tbuckley/cabot-search huggingface dataset:
DNAR-12. COMBINING TUMOUR TREATING FIELDS WITH THERAPEUTIC DNA DAMAGE RESPONSE INHIBITORS TO INCREASE POTENCY IN HIGH-GRADE GLIOBLASTOMAS USING CLINICALLY RELEVANT EX-VIVO GLIOMA STEM CELL MODELS
Authors: Aurelie Vanderlinden, Ola Rominiyi, Spencer Collis, Callum Jones, Katie Myers, Connor McGarrity - Cottrell
Journal: Neuro-Oncology (2022)

Abstract High-grade gliomas are the most common and aggressive type of primary brain cancer. Despite maximal surgical resection, followed by chemotherapy and radiotherapy, overall survival for patients remains between 10-16 months, with limited improvement in survival rates over the last 40 years. This highlights an urgent unmet clinical need to develop more effective therapeutic interventions for these devastating tumours.Tumour-Treating Fields (TTFields), which deliver low-intensity (1–3V/cm) intermediate-frequency (100–300kHz) alternating electric fields to localised tumour sites, represents an exciting new clinically-approved fourth modality for the treatment of high-grade gliomas, with randomised clinical trial evidence supporting improved overall survival (20.9 vs 16.0 months). Whilst TTFields are primarily thought to mediate their anti-cancer effects by disrupting mitotic tubulin dimer alignment leading to abnormal chromosomal segregation and mitotic cell death, recent data suggests that TTFields may also attenuate DNA damage repair efficiency and replication fork dynamics. We therefore hypothesised that combining TTFields with therapeutic DNA damage response inhibitors (DDRi), to develop next generation multimodal therapy regimes, would enhance TTFields potency in glioma cells either alone, or in combination with current standard-of-care chemoradiotherapy. To assess this, we employed clinically-relevant patient-derived primary glioma stem cell (GSC) models that represent both inter-patient and intra-tumoural heterogeneity, including unique ex-vivo models of post-surgical residual disease. We show that combining TTFields with radiation and clinically approved PARP inhibitor therapy leads to significantly increased amounts of DNA damage with concurrent decreased clonogenic survival in GSCs. Furthermore, we have shown similar impressive potency when TTFields treatments are combined with ATR inhibitors that are currently being assessed in various global clinical trials for other cancers. Overall, these exciting findings support further assessment of TTFields and DDRi combinations to underpin future clinical trials combining TTFields with clinically approved DDRi to improve outcomes for patients with currently incurable high-grade gliomas.
SURG-21. DEVELOPMENT OF MICROSURGICAL FORCEPS EQUIPPED WITH HAPTICS TECHNOLOGY FOR IN SITU DIFFERENTIATION OF TUMOR TISSUE FROM NORMAL BRAIN DURING MICROSURGERY BY TISSUE STIFFNESS
Authors: Taketo Ezaki, Kohki Kishima, Eriel Pareira, Shunsuke Shibao, Takuya Matsunaga, Yohei Kitamura, Kento Takahara, Oltea Sampetrean, Kouhei Ohnishi, Masahiro Toda, Tomoyuki Shimono, Hikaru Sasaki
Journal: Neuro-Oncology (2022)

Abstract Neurosurgeons perform tumor resection based on their tactile perception. However, many years of experience and training are required to appropriately differentiate tumor tissue from surrounding parenchymal tissue. It was reported that the stiffness of human cancer tissue strongly correlates with pathological tissue and it can be used as a biomarker. Comprehensive analysis also revealed that the molecular expression differs greatly between hard and soft tumors.Haptics technology measures and uses the stimulus that causes the sensation as a physical quantity. Force and tactile sensation is a sensation caused by mechanical contact with an object. Real Haptics is our main research field, which is a general term for technologies that quantify and utilize the force-tactile stimuli generated by contact with objects that exist in the real world and / or the virtual world.We have developed a microsurgical forceps equipped with haptics technology to differentiate tumor tissue from surrounding brain tissue during tumor dissection. We generated and used three glioblastoma cell lines (SF126, U87, U251) expressing proteins of firefly luciferase and mCherry. Each cell line was transplanted into forebrain of 5 nude mice. Tumor progression was regularly monitored with In Vivo Imaging System (IVIS) and mice were euthanized at the appropriate stage. Tumor and normal brain stiffness were measured by using the Master-slave integrated haptic forceps device. Importantly, all of the three glioblastomas were shown to be harder than the normal brain (p=0.047). The median stiffness of each tissue was as follows. Normal brain (n=15): 149.98 N/m, SF126 (n=5): 207.70 N/m, U87 (n=5): 214.40 N/m, U251 (n=5): 188.86 N/mThis pilot study showed that brain tumors could be differentiated by their stiffness from normal brain, and the forceps equipped with haptics technology might help the neurosurgeons to dissect tumor margin along the appropriate plane.
RBIO-02. ACTIVATION OF GABAA RECEPTORS WITH A NON-TOXIC, BRAIN PENETRANT SMALL MOLECULE SENSITIZES LUNG ADENOCARCINOMA PRIMARY AND BRAIN METASTATIC TUMOR CELLS TO RADIATION VIA AUTOPHAGY INDUCTION
Authors: Debanjan Bhattacharya, Riccardo Barille, Donatien Kamdem Toukam, Vaibhavkumar Gawali, Laura Kallay, Taukir Ahmed, James Cook, Aniruddha Karve, Pankaj Desai, Mario Medvedovic, Daniel Pomeranz Krummel, Soma Sengupta
Journal: Neuro-Oncology (2022)

Abstract Most advanced-stage non-small cell lung cancer (NSCLC) patients have brain metastases that render a dismal prognosis. Treatment of metastatic brain lesions from NSCLC and other tumor types include radiation as part of a multimodal treatment regimen. Challenges in the application of radiotherapy include overcoming radiation resistance and reducing associated co-morbidities. Non-toxic therapeutics capable of sensitizing tumors to radiation are needed to improve survival and mitigate radiation side-effects. Many CNS and solid systemic tumors express ligand-gated ion channels, which may contribute to tumor growth. Leveraging ion channels is therefore a potential way of diminishing the spread of cancer. We find that NSCLC and its brain metastases express subunits of the type-A GABA-gated chloride channel or GABAA receptor. Importantly, patient-derived NSCLC cells have functional GABAA receptors. We identified a brain penetrant, small molecule activator of GABAA receptors (AMLAL-101), which alone impairs the viability of both primary NSCLC cells and brain metastatic cells. In addition, AMLAL-101 combined with radiation is a highly potent inducer of NSCLC cell death and clonogenic arrest. Using a human ex vivo model of NSCLC-on-chip, we assessed the efficacy and toxicity of AMLAL-101 relative to Docetaxel, an antimicrotubular agent used in treating advanced NSCLC. AMLAL-101 is as potent as Docetaxel but does not exhibit its toxic side effects. AMLAL-101 also potentiates radiation in vivo, significantly reducing lung adenocarcinoma xenograft tumor growth in mice, equivalent to docetaxel plus radiation. Mechanistically, AMLAL-101 activates GABAA receptors in NSCLC and synergizes with radiation by inducing an autophagic response that includes: (i) stabilization of Beclin-1, BNIP3L/NIX, and GABARAP; (ii) ATG7 upregulation; and (iii) utilization of ubiquitin-binding protein p62. Activating GABAA receptors in NSCLC and other tumor types may improve radiation efficacy and mitigate its toxic side effects in treating brain metastases.
TMIC-09. HV1 PROTON CHANNELS PROMOTE MYELOID INFILTRATION AND GLIOMA PROGRESSION
Authors: Jiaying Zheng, Lingxiao Wang, Katayoun Ayasoufi, Shunyi Zhao, Emma Goddery, Cori Fain, Aaron Johnson, Long-Jun Wu
Journal: Neuro-Oncology (2022)

Abstract Myeloid cells comprising up to 50% of total tumor mass in glioblastoma (GBM) contribute to tumor progression and immunosuppression. Restraining glioma-induced myeloid cell infiltration increases functional T cells within the tumors, improves the efficacy of checkpoint blockade, and significantly extends mouse survival. Here, we focus on an ion channel, voltage-gated proton channel Hv1, which is mainly expressed in myeloid cells and shapes the physiological functions of myeloid cells. Our bioinformatics analysis demonstrated that elevated Hv1 expression in the tumor mass correlates with poor disease prognosis in patients. Using the leading immunocompetent model of GBM in mice, we showed that Hv1 knockout mice (Hv1-/-) exhibit slower glioma progression and prolonged survival. Notably, in vivo two-photon imaging, immunofluorescence, and full-spectrum flow cytometry revealed that Hv1-/- mice have reduced monocyte/macrophage infiltration, higher frequency of MHCII+ among all infiltrating myeloid cells, and increased PD-1+CD4+ T cells in the tumor-burdened hemisphere. As a result, we combined anti-PD-1 treatment with Hv1 knockout in the middle stage of glioma, and found that approximately 30% of Hv1-/- mice were cured. Together, our results demonstrated that Hv1 regulates myeloid infiltration and could be a novel therapeutic target for the treatment of GBM.
PATH-42. DIAGNOSIS AND PROGNOSTICATION OF AN ATYPICAL ADULT PRESENTATION OF DIFFUSE LEPTOMENINGEAL GLIONEURONAL TUMOR (DLGNT) BY METHYLATION PROFILING
Authors: Nishika Karbhari, Alissa Thomas
Journal: Neuro-Oncology (2022)

Abstract BACKGROUND Diffuse leptomeningeal glioneuronal tumors (DLGNT) are rare central nervous system tumors first described in the 2016 WHO classification. A paucity of data exists on this tumor. This case describes an adult presentation of DLGNT, a classically pediatric tumor, and highlights the importance of genetic and epigenetic analyses in neuro-oncologic diagnoses. CASE: A 22-year-old male presented with shoulder paresthesias and back pain, progressing to bilateral leg weakness. Spine MRI demonstrated an enhancing intramedullary T8 lesion, prompting urgent laminectomy and resection. Frozen section suggested a glial neoplasm. Four-month follow-up MRI spine showed leptomeningeal dissemination at the C-spine and caudal thecal sac. CSF analysis revealed 110 mg/dL protein, 2 cells/mcl, and negative cytology. NCI methylation profiling demonstrated 1p deletion and KIAA1549:BRAF fusion, consistent with DLGNT, subtype 1, with MAPK pathway activation; Ki-67 index was 30%. Treatment with binimetinib was initiated. After 1 month of therapy, the patient is tolerating treatment and strength is improving. DISCUSSION This case describes a rare presentation of a rare tumor. DLGNT, subtype 1, has a median age of diagnosis of 5 years and an indolent course. We describe an adult patient with molecular features consistent with DLGNT subtype 1, but a high proliferative index suggesting a more aggressive growth potential. In this case, methylation profiling aided in diagnosing the tumor type and guided treatment. The KIAA1549:BRAF fusion is an activating mutation in the MAPK pathway, and binimetinib was selected as a MEK inhibitor with high CNS penetration. To our knowledge, this is the first case of an adult-onset DLGNT treated with binimetinib. Based on our single patient experience, we would advocate for methylation profiling for rare CNS tumor entities.
CTNI-38. UPDATE ON GBM AGILE: A GLOBAL, PHASE 2/3 ADAPTIVE PLATFORM TRIAL TO EVALUATE MULTIPLE REGIMENS IN NEWLY DIAGNOSED AND RECURRENT GLIOBLASTOMA
Authors: Meredith Buxton, Brian Alexander, Donald Berry, Webster Cavenee, Howard Colman, John de Groot, Benjamin Ellingson, Gary Gordon, Mustafa Khasraw, Andrew Lassman, Eudocia Lee, Wenbin Li, Michael Lim, Ingo Mellinghoff, Tom Mikkelsen, Apoorva Nelli, James Perry, Erik Sulman, Kirk Tanner, Michael Weller, Patrick Y Wen, W K Alfred Yung, Timothy Cloughesy
Journal: Neuro-Oncology (2022)

Abstract BACKGROUND GBM AGILE (Glioblastoma Adaptive, Global, Innovative Learning Environment) is a biomarker based, multi-arm, international, seamless Phase 2/3 response adaptive randomization platform trial designed to rapidly identify experimental therapies that improve overall survival and confirm efficacious experimental therapies and associated biomarker signatures to support new drug approvals and registration. GBM AGILE is a collaboration between academic investigators, patient organizations and industry to support new drug applications for newly diagnosed and recurrent GBM. METHODS The primary objective of GBM AGILE is to identify therapies that effectively improve the overall survival in patients with ND or recurrent GBM. Bayesian response adaptive randomization is used within subtypes of the disease to assign participants to investigational arms based on their performance. Operating under a Master Protocol, GBM AGILE allows multiple drugs from different pharmaceutical/biotech companies to be evaluated simultaneously and/or over time against a common control. New experimental therapies are added as information about promising new drugs is identified while therapies are removed as they complete their evaluation. The master protocol/ trial infrastructure includes efficiencies through an adaptive trial design, shared control arm and operational processes to serve the goal of helping patients receive optimal care in a fast and efficient manner. GBM AGILE has screened over 1200 patients and enrollment rates are 3 to 4 times greater than traditional GBM trials, with active sites averaging 0.75 to 1 patients/sites/month. There are 41 active sites in the US, 4 active sites in Canada and 3 active sites in Europe with more sites anticipated to open across 5 countries in Europe. Expansion to China and Australia are under progress. Through the use of improved and flexible processes, GBM AGILE serves as a global trial that supports the efficient and rapid incorporation and evaluation of new experimental therapies for patients with GBM.Clinical trial information: NCT03970447.
CNSC-12. NEURONAL DIFFERENTIATION DRIVES THE ANTI-TUMOR EFFICACY OF MEK INHIBITION IN GLIOBLASTOMA
Authors: Sabbir Khan, Emmanuel Martinez-Ledesma, Soon Young Park, Jianwen Dong, Yuji Piao, Erin Harrison, Dimpy Koul, Veerakumar Balasubramaniyan, John de Groot, W K Alfred Yung
Journal: Neuro-Oncology (2022)

Abstract Multiple genomic aberrations and distinct molecular subtypes of glioblastoma (GBM) have been identified through multi-omics analyses including single-cell genomic and epigenomic analysis. Epidermal Growth Factor Receptor (EGFR) amplification is found in nearly 50% of GBM tumors. Several EGFR inhibitors have been tested in GBM but failed to demonstrate long-term therapeutic benefit, presumably due to target heterogeneity, escape signal pathways, and acquired resistance. Therefore, we investigated downstream signaling, mitogen-activated protein kinase (MEK1/2) as a potential therapeutic target for GBM. We utilized an unbiased high-throughput screening with a panel of glioma stem-like cells (GSCs) and identified that GBM cells harboring EGFR amplification showed anti-proliferative and apoptotic cell death (sensitive) to multiple MEK inhibitors. RNA-seq analysis of cells pre- and post-treatment with trametinib, a potent MEK inhibitor, revealed an upregulation of neurogenesis and neuronal differentiation genes such as β-III tubulin, ASCL1, DLL1, DLL3, NeuroD4, PAX6 and NCAM1. In addition, downregulation of the several MEK targets including erythroblast transformation specific (ETS) family genes, particularly ETV5 was observed. We demonstrated that MEK inhibition increased neuronal differentiation demonstrated by immunofluorescence, western blot, and RT-qPCR experiments using selected differentiation markers (β-III tubulin, ASCL1, DLL3, and NeuroD4). In addition, ETV-5 knockout in GSCs by CRISPR/Cas-9 promoted the expression of neuronal differentiation genes. Oral treatment of trametinib in an orthotopic GSC xenograft model significantly improved animal survival, in which 25-30% of mice are long-term survivors. This was accompanied by decreased MEK/ERK signal and cell proliferation in tumor tissues. Thus, we demonstrated here that MEK1/2 inhibition by trametinib induces neuronal differentiation mediated through downregulation of ETV-5 in GBM, a potential novel mechanism of action of MEK1/2 signal inhibition.
CTNI-47. TUMOR TREATING FIELDS COMBINE WITH TEMOZOLOMIDE FOR NEWLY DIAGNOSED GLIOBLASTOMA: A RETROSPECTIVE ANALYSIS OF CHINESE PATIENTS
Authors: Zhiyong Qin, Lingchao Chen, Junrui Chen, Yu Yao, Jinsong Wu, Dongxiao Zhuang, Jigntao Nie
Journal: Neuro-Oncology (2022)

Abstract BACKGROUND TTFields plus Temozolomide (TTFields/TMZ) extended survival versus TMZ alone in newly diagnosed glioblastoma (GBM) patients in the EF-14 trial. We report a retrospective analysis of Chinese newly diagnosed GBM patients who received TTFields combine with TMZ treatment and traditional TMZ monotherapy from May 2019 to May 2021 in Shanghai Hua Shan hospital.METHOD: Overall survival (OS) and progression-free survival (PFS) curves were constructed using the Kaplan-Meier method. A Cox proportional hazards regression model with inverse probability of treatment weighting (IPTW) based on propensity score was used to assess the effect of TTFields and account for confounding factors. RESULT: In the preliminary analysis, the PFS in the TTFields/TMZ arm was 16 months (95% CI:9.6–24.6) versus 11 (95% CI: 9–12) with TMZ alone (p ＜0.05). Median overall survival was 21.8 months (95% CI 17.4-NA) with TTFields/TMZ versus 15 months (95% CI 13–18; HR 0.43, p ＜0.01) with TMZ alone. In the Multivariate analysis, Surgery type, STUPP scheme, IDH status, and TTFields use were identified as favorable prognostic factors. After PSM adjustment, the groups were similar, except that MGMT promoter methylation remained more in the TMZ group (12 v 32; P = 0.011). Upon IPTW Survival analysis, TTFields was associated with a significantly lower risk of death (hazard ratio [HR], 0.19 in OS (95% CI 0.09–0.41) and progression (HR, 0.35 (95% CI 0.14–0.91) compared with TMZ alone. CONCLUSION In the analysis of our single center of patients with glioblastoma, the addition of TTFields to maintenance temozolomide chemotherapy vs maintenance temozolomide alone, resulted in statistically significant improvement in progression-free survival and overall survival. These results are consistent with the outcome of EF-14.
RBIO-05. QUANTIFICATION OF TSPO EXPRESSION AND TSPO RADIOLIGAND UPTAKE IN PET IN HUMAN AND MURINE GLIOBLASTOMA ON CELLULAR LEVEL
Authors: Sabrina Kirchleitner, Laura Bartos, Joerg-Christian Tonn, Nathalie Albert, Rainer Glass, Roland Kaelin, Stefanie Quach, Fabian Binter, Adrien Holzgreve, Matthias Brendel
Journal: Neuro-Oncology (2022)

Abstract OBJECTIVE Translocator protein (TSPO) PET imaging is used in different neurological diseases and emerges as new tool for the diagnosis and therapy planning of glioma patients. Various signal sources of the TSPO-PET signal, however, hamper image interpretation and biological understanding. Here we assess the TSPO expression and ligand uptake in a murine model and human tissue derived from glioma patients. METHODS Mice with implanted GFP+ glioblastoma (n=20) or after sham implantation (n=14) were injected with the TSPO tracer [18F]GE-180 and received PET imaging. Tumors were harvested and processed to single cell suspension. Subsequently, tumors were either stained for TSPO, CD11b, ACSA2, GFAP and analyzed by flowcytometry or else magnetic cell sorting was performed to isolate tumor and CD11b+ cells that were measured by gamma counter. Multiple regression was used to determine contributions of GFP, CD11b, ACSA2 and GFAP positive cells to the total uptake. In TSPO PET-scans of glioma patients, regions with different GE-180 uptake were defined. Tumor samples (n=12) of these predefined areas were collected during surgery and analyzed by FACS as described above. RESULTS The expression of TSPO and PET signal in mice was increased in the tumor compared to tumor-free brain (SUVRGBM: 2.06 / SUVRSHAM: 0.92). FACS detected TSPO in tumor cells, microglia/macrophages and astrocytes. Tumor cells showed higher tracer uptake per cell when compared to CD11b+ cells (+31%). The contribution to the whole TSPO tracer uptake was high for tumor (β=0.41, P=0.018) and microglia/macrophages (β=0.35, P=0.042), and lowest for astrocytes (β=0.28, P=0.011). Patients with high-grade glioma indicated higher TSPO tracer uptake in GFAP+ cells when compared to CD11b+ cells and single cell uptake correlated with PET signal. CONCLUSION In experimental orthotopic glioblastoma, we could detect TSPO tracer signal at cellular resolution level. TSPO-PET can provide information about tumor and tumor-associated myeloid cells.
NIMG-17. A DEEP LEARNING MODEL FOR DISCRIMINATING TRUE PROGRESSION FROM PSEUDOPROGRESSION IN GLIOBLASTOMA PATIENTS
Authors: Mana Moassefi, Shahriar Faghani, Gian Marco Conte, Roman Kowalchuk, Sanaz Vahdati, David Crompton, Carlos Perez Vega, Ricardo Domingo Cabreja, Sujay Vora, Alfredo Quiñones-Hinojosa, Ian Parney, Daniel Trifiletti, Bradley Erickson
Journal: Neuro-Oncology (2022)

Abstract INTRODUCTION Glioblastomas (GBMs) are highly aggressive tumors. A common clinical challenge after standard of care treatment is differentiating tumor progression from treatment-related changes, also known as pseudoprogression (PsP). Usually, PsP resolves or stabilizes without further treatment or a course of steroids, whereas true progression (TP) requires more aggressive management. Differentiating PsP from TP will affect the patient's outcome. This study investigated using deep learning to distinguish PsP MRI features from progressive disease. METHOD We included newly diagnosed GBM patients who met the inclusion criteria, including a new or increasing enhancing lesion size within the original radiation field and who had clinical, medication, and any histopathology available. The interpretation of the MR images at the image inclusion time point had to be indeterminate. We labeled those who subsequently were stable or improved on imaging and clinically as PSP and those with clinical and imaging deterioration as TP. A subset of subjects underwent a second resection. We labeled these subjects as PSP or TP based on the histological diagnosis. We performed skull stripping, coregistered contrast-enhanced T1 MRIs with T2-weighted images for each patient and used them as input to a 3-D Densenet121 model. We used several augmentation techniques and five-fold cross-validation to achieve more robust predictions. RESULT We included 124 patients who met the criteria, and of those, 63 were PsP and 61 were TP. We trained a deep learning model that achieved 76.4% (ranged 70%-84%, SD 5.122) mean accuracy over the 5 folds, 0.7560(ranged 0.6553-0.8535, SD 0.069) mean AUROCC, 88.72% (SD 6.86) mean sensitivity, and 62.05%(SD 9.11) mean specificity. CONCLUSION We report the development of a deep learning model that distinguishes PsP from TP in GBM patients treated per the Stupp protocol. Further refinement and external validation are required prior to widespread adoption in clinical practice.